Machine Learning · Computer Science
Discriminative Attribution from Counterfactuals
Nils Eckstein, Alexander S. Bates, Gregory S. X. E. Jefferis, Jan Funke
2021-09-29
Machine Learning · Statistics
Learning how to explain neural networks: PatternNet and PatternAttribution
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller +3
2017-10-26
Artificial Intelligence · Computer Science
Interpreting Interpretations: Organizing Attribution Methods by Criteria
Zifan Wang, Piotr Mardziel, Anupam Datta, Matt Fredrikson
2020-04-07
Machine Learning · Computer Science
Obtaining Example-Based Explanations from Deep Neural Networks
Genghua Dong, Henrik Boström, Michalis Vazirgiannis, Roman Bresson
2025-02-28
Machine Learning · Computer Science
Visual Reasoning of Feature Attribution with Deep Recurrent Neural Networks
Chuan Wang, Takeshi Onishi, Keiichi Nemoto, Kwan-Liu Ma
2019-01-18
Computer Vision and Pattern Recognition · Computer Science
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier, Lisa M. Koch +1
2025-11-14
Machine Learning · Computer Science
Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
Shichang Zhang, Tessa Han, Usha Bhalla, Himabindu Lakkaraju
2025-05-30
Machine Learning · Computer Science
Harmonizing Feature Attributions Across Deep Learning Architectures: Enhancing Interpretability and Consistency
Md Abdul Kadir, Gowtham Krishna Addluri, Daniel Sonntag
2023-09-20
Computer Vision and Pattern Recognition · Computer Science
Sampling Matters in Explanations: Towards Trustworthy Attribution Analysis Building Block in Visual Models through Maximizing Explanation Certainty
Róisín Luo, James McDermott, Colm O'Riordan
2025-06-26
Machine Learning · Computer Science
Attribution Explanations for Deep Neural Networks: A Theoretical Perspective
Huiqi Deng, Hongbin Pei, Quanshi Zhang, Mengnan Du
2025-08-12
Computer Vision and Pattern Recognition · Computer Science
Explainable Deep Classification Models for Domain Generalization
Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi, Mehrnoosh Sameki +4
2020-03-17
Machine Learning · Computer Science
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments
Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei +4
2024-02-15
Computer Vision and Pattern Recognition · Computer Science
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings
Lukas Klein, João B. S. Carvalho, Mennatallah El-Assady, Paolo Penna +2
2023-06-16
Machine Learning · Computer Science
Attributing Learned Concepts in Neural Networks to Training Data
Nicholas Konz, Charles Godfrey, Madelyn Shapiro, Jonathan Tu +2
2023-12-29
Computer Vision and Pattern Recognition · Computer Science
Seeing in Words: Learning to Classify through Language Bottlenecks
Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum +1
2023-07-04
Computer Vision and Pattern Recognition · Computer Science
Spatio-Temporal Perturbations for Video Attribution
Zhenqiang Li, Weimin Wang, Zuoyue Li, Yifei Huang +1
2021-09-02
Machine Learning · Computer Science
Do Explanations Explain? Model Knows Best
Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari, Nassir Navab
2022-03-07
Computer Vision and Pattern Recognition · Computer Science
Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation
Sam Sattarzadeh, Mahesh Sudhakar, Anthony Lem, Shervin Mehryar +6
2020-12-29